Nicholas Schiefer, 17, is getting some lofty comparisons when he won the prestigious gold medal at the Canada-Wide Science Fair in May. The student from HTS: Holy Trinity School in Richmond Hill, Ont., created an original way to retrieve information of short documents such as tweets and news headlines through his project, Apodora, the Markov Chain-Inspired Microsearch. Apodora refers to a python species with exceptional search capabilities.

“His algorithm, unlike many others used in existing search engines, is capable of producing more accurate and meaningful search results,” says Michael Kwok, a Canada-Wide Science Fair judge, in a press release. “I expect his work will have a profound impact in both the industry and the research community.”

Ken Nickerson, a York Region Science Fair judge, remembers meeting a student like Schiefer when he was judging 20 years ago. The student was Michael Serbinis, now CEO of e-reader giant Kobo Inc. ”Nicholas has a stellar mind and the ability to execute,” Nickerson says. “He has a brilliant future worth watching and investing in.”

A student and his teacher predicted the Grade 11 student would accomplish great things, perhaps even becoming the “next Mark Zuckerberg,” CEO and founder of Facebook.

The budding scientist from Pickering, Ont., tells Our Kids about his eureka moment and how his private school education helped him on his mission to discover the next digital revolution.

Nicholas Schiefer, a Grade 11 student at HTS: Holy Trinity School in Richmond Hill, Ont., won the gold medal at both the York Region Science and Technology Fair and the annual Canada-Wide Science Fair for his Apodora project.

Q: What is your project about and what inspired it?

A: I performed my research in an area of computer science called information retrieval, or the study of constructing search engines. Specifically, I focused on an area called “microsearch,” which deals with search on very short documents such as tweets, Facebook status updates, and news headlines. Common approaches to information retrieval often make what is called the “Independence assumption” — that is, they assume that all words are completely independent in meaning from all other words. This assumption works quite well on longer documents such as web pages and news articles because the author has the opportunity to include synonyms and descriptions of the words they use. However, in microsearch applications, this assumption breaks down. Since it is assumed that there are no relationships between words, such algorithms rely on search terms actually appearing in retrieved documents. For example, a search for “cat” won’t necessarily turn up a tweet containing only the word “kitten.” In my project, I developed an information retrieval (IR) algorithm that does not make the independence assumption and instead uses statistically inferred relationships between words to give better search results.

My project was inspired by the “semantic baggage” that is associated with every word we use. When I say “elephant,” you probably don’t just think about a large, grey African mammal. Thoughts about Africa itself, conservation, poaching and endangered species might come to mind, for example. A few years ago, I was reading a book entitled Geekspeak: Why Life + Mathematics = Happiness. The British author included in this book an interesting statistical analysis of personal advertisements found in British newspapers. He discovered that the words in the advertisement made a remarkable difference in the kind of response the poster received. As it turns out, there is semantic baggage associated with everything we say, and, being somewhat curious about search, I wondered if I could use words’ semantic baggage in a search technique.

Q: What do you hope your invention will accomplish that Facebook and Twitter haven’t done so far?

A: Facebook and Twitter are amazing platforms for publishing content. Certainly, we have no trouble broadcasting information in the same way that we did when the printing press was invented. However, we’re now at the point where the amount of information that is produced, stored, and made available has exceeded our capacity to process it. I think that there is a huge amount of useful information stored in social media sites such as Facebook and Twitter, and that the current challenge is deciding what to do with it. I believe that my invention can help improve search, especially in the context of social media.

Ultimately, the goal of my invention is to improve universal access to information embedded in very short documents. In our “Information Age,” what really separates people is their access to the growing body of information available, largely online. I noticed that an increasingly large amount of content is now transmitted and received over social networks, news headlines, and other short documents.

Q: What do you think about being called the “next Mark Zuckerberg”?

A: I think that the nature of my innovation is quite different than Zuckerberg’s. The genius in his approach was largely human and founded in exclusivity; sites like Facebook already existed (think MySpace, Friendster, and the like). The key to Facebook’s success, in my opinion, was in making people want to use it. In contrast, I think that my innovation is largely algorithmic. In fact, I managed to test my ideas scientifically in a way that Zuckerberg never could. The need and desire to search for micro-content already exists. What I sought to improve was how well the results matched your information need.

Q: What sparked your interest in science?

A: It’s hard to place it exactly. I believe myself to be naturally curious about the world around us. As a child, I liked to ask the question “Why?”, and in doing so became interested in the way the world works. In addition, I had a lot of opportunities to develop my scientific curiosity with amazing parents, teachers and schools.

Q: What role did your private school education play in fostering your passion and success as a young budding scientist?

A: Holy Trinity School (HTS) has really fostered both my creativity and natural curiosity. In our science classes especially, we aren’t simply given books and notes from which we must memorize the content; we are given the opportunity to question, challenge, experiment with, and finally truly understand the material. I still remember a lab demonstrated by my Grade 9 science (and now Grade 11 biology) teacher, Mrs. Erica Auer, in which she tossed the various alkali metals into beakers of water. After learning that alkali metals are highly reactive, and become more reactive towards the bottom of the periodic table, we were able to see for ourselves that lithium merely fizzed, sodium burst into flames, and potassium released an enormous fireball on contact with water. We were then asked to explain this periodic trend, and left with a much more thorough understanding of atomic theory than we could have gleaned from a textbook alone.

HTS played a large supportive role in my success at science fairs. I found my teachers to be very understanding about all of the school I missed to attend the Canada-Wide Science Fair, for example. In fact, a number of teachers even moved some assignments around. In particular, my physics teacher and Science Olympic coach Ms. Nina Dolgovykh played a large role as my “coach.” Even though she isn’t a computer scientist, it was invaluable to have a person with science fair experience (both as a teacher and as a judge) to guide me through the process. In fact, it was Ms. Dolgovykh who persistently encouraged me for several years to pursue a science fair project before I finally decided to give it a try. I cannot explain how valuable it is to have a “tester judge” who will tell you if you’re speaking too quickly, making the font size on your poster too small, and focusing on the wrong topics. Ms. Dolgovykh helped me every step of the way, reminding me of upcoming deadlines (of which there were many), acted as an amazing cure for procrastination, encouraged and pushed me to do my best.

Q: What are your future aspirations?

A: I’m not entirely sure about the nature of my future career. I’ve dabbled in more theoretical fields, and in more applied ones, and enjoyed aspects of both. I do know that I want to study computer science and mathematics in some sort of combination, and hope to pursue some sort of graduate study in those subjects. Regardless of where I am or what I am doing, I hope that I can continue to do some sort of scientific research.

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